code: def test_iht_reproducibility():
      from sklearn.datasets import load_digits
  
      X_digits, y_digits = load_digits(return_X_y=True)
      idx_sampled = []
      for seed in range(5):
          est = RandomForestClassifier(
              n_estimators=10, random_state=seed
          )
          iht = InstanceHardnessThreshold(
              estimator=est, random_state=RND_SEED
          )
          iht.fit_resample(X_digits, y_digits)
          idx_sampled.append(iht.sample_indices_.copy())
      for idx_1, idx_2 in zip(idx_sampled, idx_sampled[1:]):
          assert_array_equal(idx_1, idx_2)
  
file_path: imbalanced-learn/imblearn/under_sampling/_prototype_selection/tests/test_instance_hardness_threshold.py
imports: import numpy
  from sklearn.ensemble import GradientBoostingClassifier, RandomForestClassifier
  from sklearn.naive_bayes import GaussianNB
  from sklearn.utils._testing import assert_array_equal
  from imblearn.under_sampling import InstanceHardnessThreshold
label_desc: Use image node_id 5 for calling a global function with example usage: test_iht_reproducibility() without return types